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Startup funding simulator

Hacker News

Startup funding simulator

Hi HN We built a tool to help founders understand how modern fundraising (with safes) works, and how much dilution you can expect when raising money. The project is open-source. The code is a mess right now, but it'll get better I promise. You can also help with that. We didn't build this to make money. We genuinely did it because we were looking for it, and couldn't find it. We're in fact in the process of fundraising for a company, and at first glance the process looks simple. Just an excel sheet will do! But then the more we dug into it and tried different simulators, the more we realized that it's more complex than it looks. We even signed up to Pulley, Carta and others just to run simulations. But they're a bit confusing. TL;DR: Understanding modern startup funding and knowing how much dilution you'll face is hard. We built a tool that'll hopefully help with that. You can add Post-money Safes, priced rounds and issue options to employees, and you can see how that affects your ownership at every step. You can also simulate an Exit scenario and see how much money you'll be left with. --- Some examples of complex stuff: - There are many different types of safes. They all convert at the first priced round, but in different ways. Some are through discount, some are uncapped, some have a fixed valuation cap, and some have both a discount and a valuation cap. - All safes (before first priced round) convert at the same time. They don't dilute each other, which is what happens in the rest of fundraising. - Investors often require you to set aside some options. This one is particularily nasty. Basically, if an investor expects you to set aside 10% as options, and expects to get 10% equity, that's what should appear in the subsequent cap table. However, calculating the options is difficult, and is often a circular calculation (even Kirsty Nathoo from YC says it's complex and avoids showing the calculation in the Safe video "Understanding SAFEs and Priced Equity Rounds") - Safes and priced rounds can have pro-rata, but don't always exercise it - Pro-ratas of safes are taken from the priced round money, so you'd expect the safe holder's equity to remain the same if they exercise it. BUT ... it gets diluted by the new options issued. - Safes can have an MFN provision, which defers the valuation discussion/calculation until the moment the priced round is about to close. With a mix of discounts, uncapped and valuation caps, it gets tricky to know which deal is "better". - ... Assumptions and limitations: - Only post-money safes and priced rounds. - No down rounds. There's a bit more complexity around liquidation preferences and anti-dilution rights - we don't support that now. It only matters if you're simulating a "bad" situation. But come on, it's a simulator — Be optimistic. - No pro-rata caps. We might add that soon, to fully support the YC standard deal. But for now, if an investor gets a pro-rata, they can exercise either all of it (keeping their original ownership) or none. - Safes' pro-ratas disappear after the first priced round. (I think this is what happens normally?) - Remaining available options get redistributed evenly at exit. - The round is the investor. For the sake of simplicity, consider "Series A" as the combination of all series A investors into one, super-investor. Let us know what you think!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: new, using, code · Missing: mac, agents, macos
83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: lua, ide, io · Missing: https docs, excited, just released
55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, way · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: make money · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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